We live in a world where on-demand services are increasingly becoming the norm. In our personal lives, we have unprecedented choice in how and when we consume film, music, and TV.

Yet as soon as we enter the office or log-on remotely, we see a stark difference in user experience, choice, and efficiency when it comes to market data consumption and pricing models. Despite all the innovations that exist within financial services, market data has stayed largely unchanged for decades.

Compound that with the increasingly complex market environment of today, with uncertainties caused by Brexit and COVID-19, it is time for a new way of thinking about data. There has never been a more crucial time to look at how we do things and innovate toward a new standard.

Changes in the last decade – can’t we do more?

As market operators and vendors realised that data was no longer just a by-product of trading and over the last decade, information has become the cornerstone to efficient execution and trading strategy. Whether it is for risk management, back-testing, hedging, or measuring the costs and quality of execution, data is key to several operations as well as navigating this post-Brexit, post-COVID environment.

As a result of the exponential growth in the demand for data, we have seen a rise in offerings from numerous operators as well as complaints about the need to ‘unbundle’ legacy data packages. This ‘package’ structure has become increasingly challenging for consumers as they contend with a lack of clarity around how valuable these large data packages are. The bundled approach has created unwieldy datasets, making it very difficult for clients to derive specific value from the information they receive.

The rising costs and complexities associated with data packages are not going away and any data provider needs to manage these issues as well as address client demand for focus, granularity, value and efficient distribution.

A model for modern users

The solution is not anything revolutionary but it is a unique one in this space. Simply put, purchasing power needs to be given back into the hands of the consumer. Clients should only have to pay for what they need when they need it.

Data vendors must also recognise that their client needs are not static. They must be agile in adapting to evolving requirements by providing flexibility by slotting datasets in and out based on what the client needs. It should be just like Apple’s transformation of the music industry which went from consumers having to buy full albums or discographies, to purchasing individual songs, creating unique playlists and listening to music in the order they want.

The best commercial models must provide customers with flexibility and choice across its product suite, allowing them to consume and license the data relevant to their businesses. Clients should be free to request specific elements, industries or market trends for analysis, ensuring they receive only the information that they need, on-demand.

Giving clients the choice to build their packages based on their needs may not sound ground-breaking, but there is a dire lack of it today. It is a straightforward yet efficient solution to a complex market environment. The market data industry needs to shift towards a far more bespoke method of consumption. Large cumbersome data packages, vendor-dictated product suites, inflexibility in delivery mechanisms and, most important of all, poor and outdated pricing methodologies, are relics no longer fit for purpose.